Comments (3)
glenn-jocher
commented on May 27, 2024
Hello!
The Programmable Gradient Information (PGI) you’re looking for, as implemented in YOLOv9, is currently not available in the YOLOv8 repository. As YOLOv9 is an experimental model trained on the YOLOv5 codebase, we recommend keeping an eye on the Ultralytics GitHub for any future updates or releases that include PGI features.
If you have more questions or need further assistance, feel free to ask! 😊
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silvada95
commented on May 27, 2024
Did you feel any difference regarding YOLOv8 when running just the Backbone in our framework?
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glenn-jocher
commented on May 27, 2024
Hey there! If you're running just the YOLOv8 backbone, you might notice differences in processing time or accuracy since it's only part of the entire architecture, and doesn't include additional layers or mechanisms that handle specific tasks like detection heads. Make sure your integration aligns with the backbone's input and output requirements for the best results! If you have specific issues or results to discuss, feel free to share! 😊
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Related Issues (20)
- Why is yolov5n better than yolov8n in my own dataset (e.g., P, R, MAP50, etc.)，even in coco128 HOT 2
- About loading model weights HOT 4
- I'm also having the same problem, I use botsort to track the target to detect the target but can't, the confidence level is also very high, the threshold setting should be fine. How to solve it, I thought it was a confidence threshold, but I can't debug it HOT 2
- yolov8 keypoint detection results HOT 2
- can anyone guide to do quantization for custom trained yolov8 HOT 2
- Implement Resnet Backbone into YOLOv3 and YOLOv5 HOT 3
- Is there any implementation of yolov8 in cpp using tensorflow lite? HOT 3
- Angle representation method of YOLOV8-obb HOT 1
- Ultralytics not working on Jetpack 6.0? HOT 1
- The YOLOv8 segmentation model with batching option doesn't run on the GPU ? HOT 1
- yolov8n's coco pre-training? HOT 2
- Can not extract predicted classes from the results as a variable. HOT 2
- Changing the Yolov8-OBB head to output Polygonal Bounding Box with Four Corners instead of Oriented Bounding Box HOT 2
- annotation type HOT 1
- How to improve the accuracy of yolov8-obb in detecting large targets HOT 2
- The parameters printed through model.info are different from those printed through the val command HOT 1
- YOLOv8 Training Your Own Dataset HOT 2
- Image prediction HOT 5
- Train the selected model structure for your dataset HOT 3
- Overfitting issues while using pre-trained weights HOT 8
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